Feature engineering and machine learning for causality assessment in pharmacovigilance: Lessons learned from application to the FDA Adverse Event Reporting System.
Please log in to take part in the discussion (add own reviews or comments).
Cite this publication
More citation styles
- please select -
%0 Journal Article
%1 journals/cbm/KreimeyerDSMRBB21
%A Kreimeyer, Kory
%A Dang, Oanh
%A Spiker, Jonathan
%A Muñoz, Monica A.
%A Rosner, Gary
%A Ball, Robert
%A Botsis, Taxiarchis
%D 2021
%J Comput. Biol. Medicine
%K dblp
%P 104517
%T Feature engineering and machine learning for causality assessment in pharmacovigilance: Lessons learned from application to the FDA Adverse Event Reporting System.
%U http://dblp.uni-trier.de/db/journals/cbm/cbm135.html#KreimeyerDSMRBB21
%V 135
@article{journals/cbm/KreimeyerDSMRBB21,
added-at = {2023-09-30T00:00:00.000+0200},
author = {Kreimeyer, Kory and Dang, Oanh and Spiker, Jonathan and Muñoz, Monica A. and Rosner, Gary and Ball, Robert and Botsis, Taxiarchis},
biburl = {https://www.bibsonomy.org/bibtex/264819dead2338780dad625489e93ecbf/dblp},
ee = {https://doi.org/10.1016/j.compbiomed.2021.104517},
interhash = {69db2ea688d9c5136c862cdfc9980fb4},
intrahash = {64819dead2338780dad625489e93ecbf},
journal = {Comput. Biol. Medicine},
keywords = {dblp},
pages = 104517,
timestamp = {2024-04-09T02:43:54.000+0200},
title = {Feature engineering and machine learning for causality assessment in pharmacovigilance: Lessons learned from application to the FDA Adverse Event Reporting System.},
url = {http://dblp.uni-trier.de/db/journals/cbm/cbm135.html#KreimeyerDSMRBB21},
volume = 135,
year = 2021
}
